Cross-Attribute Level Effects Models for Modeling Modified 5-Level Version of Eq-5d Health State Values: Is Less Still More?

Jan van Busschbach, Zhihao Yang, Kim Rand, Nan Luo

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)
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Abstract

Objectives:
Cross-attribute level effects (CALE) model has demonstrated better predictive accuracy for out-of-sample health states than the conventional additive main-effects model in cross-validation analysis of the 5-level version of EQ-5D (EQ5D-5L) composite time trade-off (cTTO) datasets. In this study, we aimed to further test the performance of CALE model using a different design and modified EQ-5D-5L states.

Methods:
A total of 29 EQ-5D-5L self-care bolt-off states, 30 EQ-5D-5L states, and 31 EQ-5D-5L vision bolt-on states were selected from the same orthogonal array. A total of 600 university students were interviewed face-to-face to value a
subset of these health states using the cTTO method. For each type of health state, we fitted both the conventional maineffects model and the CALE model. Predictive accuracy was assessed in a series of cross-validation analysis using the leave-one-state-out method.

Results:
Overall, the CALE model outperformed the conventional model for each of the 3 types of health states in predicting the cTTO values of out-of-sample health states. The prediction accuracy of using the CALE model improved with the number of dimensions in health states, for example, the MAE decreased about 24%, 67%, and 77% for the EQ-5D-5L self-care bolt-off, EQ-5D-5L, and EQ-5D-5L vision bolt-on states, respectively, when using CALE models.

Conclusion:
Our study supported the strengths of the CALE model for modelling the utility values of both original and modified EQ-5D-5L health states. Investigators with limited resources may consider using the CALE model to lower the costs
for their valuation studies for EQ-5D-5L or similar health state descriptive systems.
Original languageEnglish
Pages (from-to)865-872
Number of pages8
JournalValue in Health
Volume26
Issue number6
Early online date22 Dec 2022
DOIs
Publication statusPublished - Jun 2023

Bibliographical note

Funding Information:
Funding/Support: This work was supported by the grant 20170640 from the EuroQol Research Foundation, the Netherlands .

Funding Information:
Conflict of Interest Disclosures: Drs Yang and Luo reported receiving grants from the EuroQol Research Foundation during the conduct of the study and outside the submitted work. Dr Rand is the current Chair of the EuroQol Scientific Executive Committee. Dr Busschbach reports grants from the EuroQol Research Foundation outside the submitted work. Drs Yang, Rand, Busschbach, and Luo are EuroQol members. Dr Luo is an editor for Value in Health and had no role in the peer-review process of this article. No other disclosures were reported.Funding/Support: This work was supported by the grant 20170640 from the EuroQol Research Foundation, the Netherlands.

Publisher Copyright:
© 2023 International Society for Pharmacoeconomics and Outcomes Research, Inc.

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